2 citations · 2 across the 8 of their papers we have counts for
6 papers · 1 filter
Evolving Executable Pipeline Programs for AutoML with Language Models
Sofoklis Kitharidis, Cor J. Veenman, Jan N. van Rijn +2
Automated machine learning (AutoML) systems search for pipelines within a space of preprocessing operators, learners, and hyper-parameters specified in advance: they can select and…
Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space
Sofoklis Kitharidis, Cor J. Veenman, Thomas Bäck +1
In the context of algorithmic decision-making, fair machine learning methods often yield multiple models that balance predictive fairness and performance in varying degrees. This d…
Anomalous NO2 emitting ship detection with TROPOMI satellite data and machine learning
Solomiia Kurchaba, Jasper van Vliet, Fons J. Verbeek +1
Starting from 2021, more demanding emission restrictions were introduced for ships operating in the North and Baltic Sea waters. Since all methods currently us…
PERFEX: Classifier Performance Explanations for Trustworthy AI Systems
Erwin Walraven, Ajaya Adhikari, Cor J. Veenman
Explainability of a classification model is crucial when deployed in real-world decision support systems. Explanations make predictions actionable to the user and should inform abo…
Context-Aware Discrimination Detection in Job Vacancies using Computational Language Models
S. Vethman, A. Adhikari, M. H. T. de Boer +2
Discriminatory job vacancies are disapproved worldwide, but remain persistent. Discrimination in job vacancies can be explicit by directly referring to demographic memberships of c…
Fair Tree Classifier using Strong Demographic Parity
António Pereira Barata, Frank W. Takes, H. Jaap van den Herik +1
When dealing with sensitive data in automated data-driven decision-making, an important concern is to learn predictors with high performance towards a class label, whilst minimisin…